A variety of methods exist for classifying pixels. One type of classification entails computing a statistical probability that a pixel has a certain feature or belongs to a certain class. In some classification systems, pixel data is “walked” through decision nodes of a decision tree, until processing operations culminate at a leaf node. Associated with the leaf node is an output that is used to classify the pixel. Typical decision tree systems have shallow pipelines and are sub-optimal in their handling of operation stalls, memory contention and long-latency events.